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The need to monitor ice conditions has motivated the launch of several earth observation (EO) satellites and ice mapping applications are among the highest consumers of satellite data. However, oil and gas operations (O&G) in ice-prone (both sea ice and iceberg) environments have largely been using EO data for upstream, strategic reports on ice conditions. There are many recent and upcoming advances in EO technology that are already enabling satellites to be used for other critical operations and there is value in using satellites extensively for ice management. The remainder of this paper briefly describes these advances and their impact on detecting ice conditions to support oil and gas operations.

Declining sea ice conditions are often cited as an indicator of climate change, but limited information is available on sea ice ridges, which comprise up to 50% of ice volume in certain regions. Multi-year (MY) ridges are more hazardous barriers to navigation than first year (FY) ridges and they are more likely to survive the summer melt season, but little effort has been made to identify FY and MY ridges from remote sensing data. This paper describes an analytical method to model electromagnetic scattering from ridges around the VHF range (100–500 MHz) when ridges are modeled as a rough surface over stratified media. Models considering the macroscopic properties of FY and MY ridges relevant to VHF scatter are presented. Simulations show that FY and MY ridges have different scattering characteristics, making it possible to separate the two ice types. Future work will consider how variability in ice ridge characteristics and changes during the ice season affect the separability of FY and MY ridges based on their scattering characteristics.

Sea ice ridges pose some of the greatest threats to navigation in polar and sub-polar regions and it is important to characterize ridges using remote sensing data. First year (FY) ridges and multi-year (MY) ridges may be present in the same region, but MY ridges are stronger and have the potential to cause greater damage to vessels and structures. A new approach has been developed to model electromagnetic (EM) scattering from sea ice ridges. Ridges are represented as having a rough surface over horizontally stratified and isotropic layers. The total scatter from the ridge is the sum of the scatter from the surface and the layers. This paper provides an overview of the modeling process and provides some initial simulation results showing the impacts of radar frequency and ice salinity on the scattered wave. Ice ridge surface and structure characteristics affect the nature of the scattered signal and additional work is required to determine if it is possible to reliably distinguish between ridge types. Future work will involve simulations using more detailed modeling of ice ridge profiles to better determine how radar frequency and ice ridge structure and phenology affect ice discrimination.

The generalized function approach for modeling radio wave scattering has been used to develop expressions for the backscatter from rough surfaces and from horizontally stratified media. The research was initially used to model high frequency surface wave radar scattering from a rough ocean surface or across layers of ice covering the ocean. This paper extends the existing theory by assuming an arbitrary dielectric constant for a simple rough surface and by suggesting an approach to model the backscatter from a stratified medium that has a rough surface. When an arbitrary dielectric constant is used for the rough surface, the shape of the scattered field remains the same, but is weaker due to the transmission of energy through the surface. Scatter from rough surfaces and stratified media both can be expressed as the sum of a direct and reflected wave. This form is exploited to understand the scatter from a rough surface over layered media.

The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional ice condition simulation. The paper describes the implementation of the Los Alamos sea ice model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea ice simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as ice concentration, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea ice behavior over 7 years was simulated to analyze ice formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated ice concentration correlated well with Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Ocean and Sea Ice Satellite Application Facility (OSI-SAF) data. Visual comparison of ice thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010–2011.

Well sites, including both well pads and exploratory core holes, are small polygonal landscape disturbance features approximately one half to one hectare (0.5–1 ha) in area, resulting from oil and gas exploration activities. Automatic extraction and monitoring of such small features using remote-sensing technology at regional scales has always been desirable for wildlife habitat monitoring and environmental planning and modelling. Due to the vast disturbances of well sites in a province like Alberta, Canada, high-resolution imagery is not practical for well site extraction. For operational purposes, mid-resolution and cost-effective satellite imagery such as Landsat is the choice. However, automatic well site extraction using mid-resolution satellite imagery is a challenging task. Wells are typically less than three pixels in width and length in a Landsat multispectral image. Furthermore, the spectral contrast between the well site pixels and the surrounding areas is low due to vegetation regrowth and the...

Research on automatic detecting, tracking and characterizing extreme ice features in the Arctic is based on analyzing and processing satellite synthetic aperture radar (SAR) and optical images. Algorithms to identify ridges from very high-resolution optical data have an accuracy of 86.4% when compared to manual extraction and ridge height has been estimated from shadow. SAR signatures of various ice features have been analyzed and the results indicate that it is possible to identify rubble fields from other ice types.

Abstract P>Sea ice monitoring is an important field of scientific research and relevant to operational applications. One of the major engineering challenges in undertaking production developments in Arctic offshore regions is the frequent presence of extreme ice features that pose a hazard to facilities and surrounding subsea infrastructure. The information on extreme ice features (i.e., ridges, icebergs etc.) is important from the standpoint of potential ice load levels on fixed structures and ice scouring of seafloor facilities. Satellite observation has been shown to be useful for extracting and characterizing ice regimes. Sea ice can be monitored using satellite imagery acquired by different types of sensors: microwave radiometer, optical instrument and synthetic aperture radar (SAR). The outputs of sea ice monitoring may include various ice parameters such as edge, thickness, concentration, classification, iceberg detection, and ice statistics. This paper describes application of high and low resolution SAR imagery for sea ice monitoring and to resolve local features and extend the statistical baseline to larger regions because extreme ice features may be invisible or ambiguous with other ice features in these data. The use of higher resolution imagery allows for easier detection of ice features and provides sufficient spatial detail necessary for detecting ice features from sea ice, identification and estimation of size and geometry of ice floes and icebergs. It was demonstrated that SAR sensors with multiple resolution lead to a better understanding of ice conditions including ice edge, concentration, floe statistics, and other ice features such as icebergs. A technique based on SAR interferometry was used for identification of iceberg in sea ice as well as for extracting iceberg topography.

Abstract The analysis of historical satellite data, both radar and optical, areuseful for understanding the nature of ice conditions in Arctic regions andunderstanding the risk they pose for exploration and development. Archivesatellite data are available at no cost and can be analyzed to assess theseverity and variability of iceberg concentrations and their behavior. National ice centres have been providing charts of sea ice conditions, whichcan be analyzed to understand probabilities of encountering ice of variousconcentrations and the lengths of the open water season. The outputs ofthese analyses are useful for understanding the risk of operating in Arcticregions and for developing an ice management plan. Introduction Satellite radar and optical imagery are essential tools for understandingsea ice and iceberg conditions in frontier Arctic and sub-Arctic regions. Satellite synthetic aperture radar (SAR) imagery can be collected day or night, are relatively independent of environmental conditions, can be collectedthrough fog and cloud cover and provide information over remote areas at noadditional cost. There is a substantial archive of low resolution imageryavailable and there is a growing number of sensors available for newacquisitions. Optical imagery, when available, are excellent forproviding detailed information on ice features such as sea ice ridges andiceberg sizes. Low resolution optical data are collected continuously, medium resolution data is available close to shore and high resolution imagescan be acquired from a large number of sensors. Historic satellite data are used to develop an understanding of the severityand variability of ice conditions in an area. This information serves asan input for the design of structures and selection of vessels that can beutilized in an area as well for development of an ice management plan anddefining the operational window. New image acquisitions are an important part of the detection component ofan operational ice management plan. Surveillance in certain marginal icezones, such as the Grand Banks, do not rely on satellite imagery since they areclose to shore and reconnaissance can be carried out almost exclusively usingplatform radar and vessel and aerial surveillance. However, the costs ofthis approach grow in remote areas and satellite SAR data have been used inaddition to platform radar to support operations in new Arctic explorationregions.

A remote sensing technique, based on processing satellite altimeter data, for iceberg detection was validated and implemented for operational iceberg monitoring. Algorithms for altimeter data preprocessing and analysis were developed to efficiently detect icebergs and eliminate false detections caused by signal noise and the presence of small islands. Results of iceberg detection for application in ship navigation are demonstrated.

Two synthetic aperture radar (SAR) datasets with validated icebergs in sea ice were analyzed. A qualitative assessment of the data using false colour visualization methods for dual polarization SAR was conducted indicating that icebergs had an improved visually discernable signature from the background over single polarization SAR.A quantitative analysis was completed to exploit these observations. The algorithm development was focused on detection, false alarm removal and false alarm prioritization. The prototype software package developed around these algorithms presently supports RADARSAT-2 Wide and TerraSAR-X Stripmap imagery.

Abstract Characterization of the ice environment is an essential step in the probabilistic design approach of Arctic offshore structures. Uncertainty here could lead to overly conservative designs and higher than necessary cap-ex. Inclusion of an effective ice management strategy further mitigates risk and cost. Both tactical and historical knowledge of the ice environment can be achieved cost effectively using space-based surveillance or Earth Observation (EO). The mapping and monitoring of ice visited regions is a fundamental application area for EO, in particular Synthetic Aperture Radar (SAR) missions. It is an all-weather, day-and-night, geographically independent sensor. Spaceborne SAR mapping of ice has been available since the 1970s; however routine SAR monitoring was not possible until the launch of Europe's ERS-1 satellite in 1992. This event also heralded in an era of large scale archiving of radar data. In addition to chart data available through various national ice centres, there is now an archive of almost 20 years of raw satellite radar data that can be used to create highly detailed historical maps of ice and icebergs to aid in the design process. Over the past 5–10 years, the number of radar satellites has quadrupled and technical capabilities have increased by an order of magnitude. Weekly surveillance has been replaced with daily and performance metrics are approaching 100%. Satellites are now a reliable, effective tool for a large portion of a project's life cycle - from exploration, to developing a design basis to production. Its prevalence within the industry is growing. This paper will highlight advances in satellite monitoring, new pricing policies to increase uptake, and recent experience using satellite SAR operationally in northern oil and gas projects. Background In conducting safe and cost effective operations, ice management and risk mitigation practices are integral to operations. The first element of the ice management plan is detection of ice and icebergs. This provides a basis for all subsequent ice management actions such as towing and suspension of operations. Comprehensive explanations of the ice management process and technologies that can be used to facilitate an ice management plan were detailed by Randell et al. (2009). Satellite SAR is well suited to map and monitor icebergs and sea ice due to its ability to provide images day or night, through cloud or fog, independent of environmental conditions. Satellite SAR mapping of ice has been available since the 1970s, although routine SAR monitoring of ice was only made possible in the 1990s with the launch of the European satellite ERS-1 in 1992. This satellite also heralded in an era of large scale data archiving of radar data. In addition to data available through various national ice centres, there is an archive of almost 20 years of raw satellite radar data that can be used to create highly detailed historical maps of ice and icebergs to aid in the design process. Many existing and almost all of the new SAR satellites are "operations ready" in that they provide their data in Near-Real- Time (NRT) with imagery available via the internet within hours of acquisition. The next generation of SARs to be launched within the next few years are specifying imagery delivery times of less than one hour; an investment in a ground station facility can allow data provision in minutes of acquisition. With these capabilities, SAR can be used effectively by the industry, with particular effectiveness in northern resource development. The increasing prevalence of SAR, along with lower data costs and flexible data policies will lead to increased use.

Abstract The characterization of the ice environment is a necessary step in the probabilistic design approach of Arctic offshore structures. Without such knowledge, design uncertainty is high with the result being overly conservative designs with higher build costs to deal with the uncertainty associated with sea ice and iceberg loads. In addition to knowledge of the ice environment, the addition of ice management to operations leads to a lower risk of ice impact. When ice management is considered at the design stage, additional design concepts may be considered, which may also lead to lower build costs. A critical component to an effective ice management plan is tactical knowledge of the ice environment. Both tactical and historical knowledge of the ice environment can be achieved cost effectively using satellite monitoring. This paper examines the evolution of satellite SAR-based monitoring of sea ice and icebergs to support Arctic offshore operations, particularly for the oil and gas industry. The presentation will demonstrate, at a high level, how these data might be used by the industry, and how recent advances in satellite mapping technology add value to these services. Background In conducting safe and cost effective operations, ice management and risk mitigation practices are integral to operations. The key and primary element of the ice management plan is the detection and subsequent mapping of ice and iceberg locations, since this provides a fundamental basis for all subsequent ice management decision making such as towing and suspension of operations. Comprehensive explanations of the ice management process and technologies that can be used to facilitate an ice management plan were detailed by Randell et al. (2009). Satellite Synthetic Aperture Radar (SAR) is naturally applicable to map and monitor icebergs and sea ice due to its ability to provide images day or night, through cloud or fog, and various wind conditions. Satellite SAR mapping of ice has been available since the 1970s, although routine SAR monitoring of ice was only made possible in the 1990s with the launch of the European satellite ERS-1 in 1992. This satellite also heralded in an era of large scale data archiving of radar data. In addition to data available through various national ice centres, there is now available an archive of almost 20 years of raw satellite radar data that can be used to create highly detailed historical maps of ice and icebergs to aid in the design process. Many existing and almost all of the new SAR satellites are ‘operational’ in that they provide their data in a near-real-time (NRT) mode, with imagery available via the internet within hours of acquisition. The latest generation of SARs that will be launched within the next few years are specifying imagery delivery times of less than one hour; an investment in a ground station facility can allow data provision in minutes of acquisition. With these capabilities, SAR can be used effectively by the industry to aid in Arctic resource development. The increasing prevalence of SAR, along with lower data costs and more flexible data policies will lead to increased use by the industry into the future.

Abstract In August 2010 a 265 km2 ice island calved from the Petermann Glacier innorthern Greenland. Soon after the initial calving event the mass broke intoseveral pieces, some of which exited Baffin Bay and drifted south toward theLabrador coast. By June 2011 PII-A, a large fragment of the initial PetermannIce Island, was situated offshore Labrador and in one week it had moved 225 kmdown the coast. Concern arose that if PII-A continued its trajectory it couldreach the Grand Banks by August 2011, posing a potential risk for existinginfrastructure in the offshore region of Newfoundland. To properly assess thepotential risk a realistic estimate of ice mass was necessary. This in turnrequired field measurements of the ice islands thickness. A three-day field program was carried out on the Petermann Ice Islands, PII-A and PII-A-a, from June 17–19, 2011. At this time PII-A and PII-A-a weresituated offshore Labrador, Canada, approximately 100 km northeast of the townof Rigolet. Geophysical survey methods, including Ground Penetrating Radar(GPR) and Seismic Reflection, were used to identify the base of the islands andobtain ice thickness measurements at various locations. Eight satellitetracking beacons were deployed on PII-A and one was deployed on PII-A-a. Ablation data, photographs and video footage were also obtained during theprogram. On July 22, 2011, PII-A was revisited while it was situated off thesouthern Labrador coast. GPR measurements were acquired at the pre-existingstations; the measurements allowed for deterioration rates due to surface andbasal melting to be calculated for PII-A. Results of the field measurementsindicate that ice thickness varied between 50 to 80 m on PII-A; the thicknessof PII-A-a was 30 m at a single survey location. Surface melt rates of 2.7–6.3cm day-1 were observed over a 1-day period in June. For the 35-day periodbetween June and July visits, average surface and basal melt of 5.0 cm day-1and 3.4 cm day-1, respectively, were calculated.